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Guojian Zou
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2020 – today
- 2024
- [j9]Guojian Zou, Ziliang Lai, Ting Wang, Zongshi Liu, Jingjue Bao, Changxi Ma, Ye Li, Jing Fan:
Multi-task-based spatiotemporal generative inference network: A novel framework for predicting the highway traffic speed. Expert Syst. Appl. 237(Part C): 121548 (2024) - [j8]Ting Wang, Dong Ngoduy, Guojian Zou, Takao Dantsuji, Zongshi Liu, Ye Li:
PI-STGnet: Physics-integrated spatiotemporal graph neural network with fundamental diagram learner for highway traffic flow prediction. Expert Syst. Appl. 258: 125144 (2024) - [j7]Guojian Zou, Ziliang Lai, Ting Wang, Zongshi Liu, Ye Li:
MT-STNet: A Novel Multi-Task Spatiotemporal Network for Highway Traffic Flow Prediction. IEEE Trans. Intell. Transp. Syst. 25(7): 8221-8236 (2024) - [i1]Ting Wang, Ye Li, Rongjun Cheng, Guojian Zou, Takao Dantsuji, Dong Ngoduy:
Knowledge-data fusion oriented traffic state estimation: A stochastic physics-informed deep learning approach. CoRR abs/2409.00644 (2024) - 2023
- [j6]Bo Zhang, Yuan Liu, Ruihan Yong, Guojian Zou, Ru Yang, Jianguo Pan, Maozhen Li:
A spatial correlation prediction model of urban PM2.5 concentration based on deconvolution and LSTM. Neurocomputing 544: 126280 (2023) - [j5]Ting Wang, Meiting Tu, Hao Lyu, Ye Li, Olivier Orfila, Guojian Zou, Dominique Gruyer:
Impact Evaluation of Cyberattacks on Connected and Automated Vehicles in Mixed Traffic Flow and Its Resilient and Robust Control Strategy. Sensors 23(1): 74 (2023) - [j4]Guojian Zou, Ziliang Lai, Changxi Ma, Meiting Tu, Jing Fan, Ye Li:
When Will We Arrive? A Novel Multi-Task Spatio-Temporal Attention Network Based on Individual Preference for Estimating Travel Time. IEEE Trans. Intell. Transp. Syst. 24(10): 11438-11452 (2023) - [c3]Guojian Zou, Jing Fan, Honggang Wang, Changxi Ma, Ting Wang, Ye Li:
Multi-Task-Based Spatio-Temporal Generative Inference Network for Predicting Highway Traffic Speed. ITSC 2023: 3247-3252 - [c2]Ailing Yin, Xiaohong Chen, Guojian Zou:
A Fusion Deep Learning Network for Shared e-Bike Demand Prediction with Spatiotemporal Dependencies. ITSC 2023: 3390-3395 - [c1]Guojian Zou, Ting Wang, Honggang Wang, Jing Fan, Ye Li:
How to Accurately Predict Traffic Speed Using Simple Input Variables? A Novel Self-Supervised Spatio-Temporal Bilateral Learning Network. ITSC 2023: 4657-4662 - 2022
- [j3]Bo Zhang, Guojian Zou, Dongming Qin, Qin Ni, Hongwei Mao, Maozhen Li:
RCL-Learning: ResNet and convolutional long short-term memory-based spatiotemporal air pollutant concentration prediction model. Expert Syst. Appl. 207: 118017 (2022) - 2021
- [j2]Guojian Zou, Bo Zhang, Ruihan Yong, Dongming Qin, Qin Zhao:
FDN-learning: Urban PM2.5-concentration Spatial Correlation Prediction Model Based on Fusion Deep Neural Network. Big Data Res. 26: 100269 (2021)
2010 – 2019
- 2019
- [j1]Dongming Qin, Jian Yu, Guojian Zou, Ruihan Yong, Qin Zhao, Bo Zhang:
A Novel Combined Prediction Scheme Based on CNN and LSTM for Urban PM2.5 Concentration. IEEE Access 7: 20050-20059 (2019)
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